• Journal of Korean Tunnelling and Underground Space Association
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• v.11 no.4
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• pp.395-401
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• 2009

One of the key design factors for the ventilation and safety system at extra long tunnel is the airflow velocity induced by the natural ventilation force. Despite of the importance, it has not been widely studied due to the complicated influencing variables and the relationship among them is difficult to quantify. At this moment none of the countries in the world defines its specific value on verified ground. It is also the case in Korea. The recent worldwide disasters by tunnel fires and demands for better air quality inside tunnel by users require the optimization of the tunnel ventilation system. This indicates why the natural ventilation force is necessary to be thoroughly studied. This paper aims at predicting the natural ventilation force at a 11 km-long tunnel which is in the stage of detailed design and will be the longest vehicle tunnel in Korea. The concept of barometric barrier which can provide the maximum possible natural ventilation force generated by the topographic effect on the external wind is applied to estimate the effect of wind pressure and the chimney effect caused by the in and outside temperature difference is also analyzed.

• Journal of the Korean Society of School Health
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• v.14 no.1
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• pp.131-143
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• 2001

The primary aim of this dissertation is to contribute to the improvement of methods in physical examination by providing quality information for the current school system and advice for improving status. Present status, controversial points and possible remedies in physical examination were analyzed on a frequency and percentage basis. An $x^2$-test was used to verify the statistics between the results from the examination and each variable. In case of multiple categories of variables, an $x^2$ cs was adopted. Chronological data as well as both total and sampling physical examination data verified the statistics using an $x^2$-test. This thesis is based both on the data from middle school health care specialists in Gyunggi Province and on the analysis of physical examinations reported from local schools to the municipal education agency from 1997 to 1999. The results of the study are as follows: First, according to the survey, only 29.0% of the total schools had their school doctors examine all the students while most of the educational institutions failed to implement the whole process of physical examination on the list. It also turned out that the more students the schools have, the lower the rate of implementation of physical examination by school doctors(p=0.014). Second, the average time a school doctor spends for checkup turned out to be approximately 1.7 minutes per student This means that the quality of the physical examination is not guaranteed in the process. Third, 47.7% of those surveryed say that a dental examination was performed, each taking 21.24 seconds on average. In addition, it shows that some 31.5% wanted to have a task force team for dental checkups at the local health center. Given the fact that dental caries among students is progressively on the rise, the dental health centers that are now set up in some elementary schools should be expanded to cover the whole educational institution in order to raise awareness of the importance of dental care. Fourth, 48.5% of those surveyed say that a comprehensive physical examination should be adopted to promote the health of high schoolers. Since it takes a lot of public funds to implement a comprehensive method, it is essential to make sure that in-depth studies should be based on the frequency and methods of physical examination. Fifth, regarding such diseases among 3rd year middle school students in 1999, statistics shows that there was a slight difference in the prevalence rate of color blindness, and allergic diseases for male students ; and color blindness, hearing disturbance and allergic disease for female students. For those items, however, it is too little to say that there is a significant difference and accordingly it is assumed to be a problem of the measuring process. Sixth, the result of analysis on the sample physical examination and the total physical examination of the year 1999 shows as follows: For male students in the 3rd year of middle school, a slight difference appeared to those students in 11 items including eye problems and eye disease, otitis media, tonsillar hypertrophy, spinal shape, respiratory urinary allergic disease and other abnormal diseases(p<0.05). Particularly, the prevalence rate between students with and without disease was shown to be two times more in the following: eye problems, otitis media, tonsill hypertrophy, allergic diseases, etc. For female students in the 3rd year, prevalence rate showed little difference in 14 items(p<0.05). For items including eye problem, otitis media, tonsill hypertrophy, allergic disease, etc. it was shown that the rate was two times more between students with and without diseases. Physical examinations under the current school system are not producing any fundamental results for the health of the students. Methods and results are not trustworthy. Accordingly, a drastic overhaul of the current practices is needed in frequency, methods and items on the list in order to promote the health of the students. Cost-benefit studies as well as political considerations to ensure the development of efficient methods for physical examination are urgently needed at this moment.

• Journal of Korean Library and Information Science Society
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• v.11
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• pp.69-99
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• 1984

A dramatic development in the new technology of copying materials has presented us with massive problems on reconciling the conflicts between copyright owners and potential users of copyrighted materials. The adaptation to this changing condition led some countries to revise their copyright laws such as in the U. S. in 1976 and in Korea in 1984 for merging with the international or universal copyright conventions in the future. Copyright defined as exclusive rights given to copyright owners aims to secure a fair return for an author's creative labor and to stimulate artistic creativity for the general public good. The exclusive rights on copyrightable matters, generally for reproduction, preparation of derivative works, public distribution, public performance, and public display, are limited by fair use for scholarship and criticism and by library reproduction for its preservation and interlibrary loan. These limitations on the exclusive rights are concerned with all aspects of library services and cause a great burden on librarian's daily duty to provide balance between the rights of creators and the needs of library patrons. The fair use as one of the limitations on it has been coupled with enormous growth of a new technology and extended from xerography to online database systems. The implementation of the fair use and library reprography in Korean law to the local practices is examined on the basis of the new American copyright act of 1976. Under the draft revision of Korean law, librarians will face many potential problems as summarized below. 1. Because the new provision of 'life time plus 50 years' will tie up substantial bodies of material longer than the old law, until that date librarians would need permissions from the owners and should pay attention to the author's death date. 2. Because the copyright can be sold, distributed, given to the heirs, donated, as a whole or a part, librarians should chase down the heirs and other second owners. In case of a derivative work, this is a real problem. 3. Since a work has its protection from the moment of its creation, the coverage of copyrightable matter would be extended to the published or the unpublished works and librarian's work load would be heavier. Without copyright registration, no one can be certain that a work is in the public domain. Therefore, librarians will need to check with an authority. 4. For implementation of limitations on exclusive rights, fair use and library reproduction for interlibrary loan, there can be no substantial aggregate use and there can be no systematic distribution of multicopies. Therefore, librarians should not substitute reproductions for subscriptions or purchases. 5. For the interlibrary loan by photocopying, librarians should understand the procedure of royalty payment. 6. Compulsory licenses should be understood by librarians. 7. Because the draft revision of Korean law is a reciprocal treaty, librarians should take care of other countries' copyright law to protect foreign authors from Korean law. In order to solve the above problems, some suggestions are presented below. 1. That copyright clearinghouse or central agency as a centralized royalty payment mechanism be established. 2. That the Korean Library Association establish a committee on copyright. 3. That the Korean Library Association propose guidelines for each occasion, e.g. for interlibrary loan, books and periodicals and music, etc. 4. That the Korean government establish a copyright office or an official organization for copyright control other than the copyright committee already organized by the government. 5. That the Korean Library Association establish educational programs on copyright for librarians through seminars or articles written in its magazines. 6. That individual libraries provide librarian's copyright kits. 7. That school libraries distribute subject bibliographies on copyright law to teachers. However, librarians should keep in mind that limitations on exclusive rights are not for an exemption from library reprography but as a convenient access to library resources.

• Management & Information Systems Review
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• v.22
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• pp.137-165
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• 2007

It seems high time to increase productivity by adopting e-business to overcome challenges posed by both external factors including the appreciation of Korean won, oil hikes and fierce global competition and domestic issues represented by disparities between large corporations and small and medium enterprises (SMEs), Seoul metropolitan and local cities, and export and domestic demand all of which weaken future growth engines in the Korean economy. The demands of the globalization era are for innovative changes in businessprocess and industrial structure aiming for creating new values. To this end, e-business is expected to play a core role in the sophistication of the Korean economy through new values and innovation. In order to examine business performance in e-business-adopting industries, this study analyzed the home shopping industry by closely looking into the financial ratios including the ratio of net profit to sales, the ratio of operation income to sales, the ratio of gross cost to sales cost, the ratio of gross cost to selling, general and administrative (SG&A) expense, and return of investment (ROI). This study, for best outcome, referred to corporate financial statements as a main resource to calculate financial ratios by utilizing Data Analysis, Retrieval and Transfer System (DART) of the Financial Supervisory Service, one of the Korea's financial supervisory authorities. First of all, the result of the trend analysis on the ratio of net profit to sales is as following. CJ Home Shopping has registered a remarkable increase in its ratio of net profit rate to sales since 2002 while its competitors find it hard to catch up with CJ's stunning performances. This is partly due to the efficient management compared to CJ's value of capital. Such significance, if the current trend continues, will make the front-runner assume the largest market share. On the other hand, GS Home Shopping, despite its best organized system and largest value of capital among others, lacks efficiency in management. Second of all, the result of the trend analysis on the ratio of operation income to sales is as following. Both CJ Home Shopping and GS Home Shopping have, until 2004, recorded similar growth trend. However, while CJ Home Shopping's operating income continued to increase in 2005, GS Home Shopping observed its operating income declining which resulted in the increasing income gap with CJ Home Shopping. While CJ Home Shopping with the largest market share in home shopping industryis engaged in aggressive marketing, GS Home Shopping due to its stability-driven management strategies falls behind CJ again in the ratio of operation income to sales in spite of its favorable management environment including its large capital. Companies in the Group B were established in the same year of 2001. NS Home Shopping was the first in the Group B to shift its loss to profit. Woori Home Shopping has continued to post operating loss for three consecutive years and finally was sold to Lotte Group in 2007, but since then, has registered a continuing increase in net income on sales. Third of all, the result of the trend analysis on the ratio of gross cost to sales cost is as following. Since home shopping falls into sales business, its cost of sales is much lower than that of other types of business such as manufacturing industry. Since 2002 in gross costs including cost of sales, SG&A expense, and non-operating expense, cost of sales turned out to have remarkably decreased. Group B has also posted a notable decline in the same sector since 2002. Fourth of all, the result of the trend analysis on the ratio of gross cost to SG&A expense is as following. Due to its unique characteristics, the home shopping industry usually posts ahigh ratio of SG&A expense. However, more than 80% of SG&A expense means the result of lax management and at the same time, a sharp lower net income on sales than other industries. Last but not least, the result of the trend analysis on ROI is as following. As for CJ Home Shopping, the curve of ROI looks similar to that of its investment on fixed assets. As it turned out, the company's ratio of fixed assets to operating income skyrocketed in 2004 and 2005. As far as GS Home Shopping is concerned, its fixed assets are not as much as that of CJ Home Shopping. Consequently, competition in the home shopping industry, at the moment, is among CJ, GS, Hyundai, NS and Woori Home Shoppings, and all of them need to more thoroughly manage their costs. In order for the late-comers of Group B and other home shopping companies to advance further, the current lax management should be reformed particularly on their SG&A expense sector. Provided that the total sales volume in the Internet shopping sector is projected to grow over 20 trillion won by the year 2010, it is concluded that all the participants in the home shopping industry should put strategies on efficient management on costs and expenses as their top priority rather than increase revenues, if they hope to grow even further after 2007.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.1-32
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• 2018

In addition to stakeholders including managers, employees, creditors, and investors of bankrupt companies, corporate defaults have a ripple effect on the local and national economy. Before the Asian financial crisis, the Korean government only analyzed SMEs and tried to improve the forecasting power of a default prediction model, rather than developing various corporate default models. As a result, even large corporations called 'chaebol enterprises' become bankrupt. Even after that, the analysis of past corporate defaults has been focused on specific variables, and when the government restructured immediately after the global financial crisis, they only focused on certain main variables such as 'debt ratio'. A multifaceted study of corporate default prediction models is essential to ensure diverse interests, to avoid situations like the 'Lehman Brothers Case' of the global financial crisis, to avoid total collapse in a single moment. The key variables used in corporate defaults vary over time. This is confirmed by Beaver (1967, 1968) and Altman's (1968) analysis that Deakins'(1972) study shows that the major factors affecting corporate failure have changed. In Grice's (2001) study, the importance of predictive variables was also found through Zmijewski's (1984) and Ohlson's (1980) models. However, the studies that have been carried out in the past use static models. Most of them do not consider the changes that occur in the course of time. Therefore, in order to construct consistent prediction models, it is necessary to compensate the time-dependent bias by means of a time series analysis algorithm reflecting dynamic change. Based on the global financial crisis, which has had a significant impact on Korea, this study is conducted using 10 years of annual corporate data from 2000 to 2009. Data are divided into training data, validation data, and test data respectively, and are divided into 7, 2, and 1 years respectively. In order to construct a consistent bankruptcy model in the flow of time change, we first train a time series deep learning algorithm model using the data before the financial crisis (2000~2006). The parameter tuning of the existing model and the deep learning time series algorithm is conducted with validation data including the financial crisis period (2007~2008). As a result, we construct a model that shows similar pattern to the results of the learning data and shows excellent prediction power. After that, each bankruptcy prediction model is restructured by integrating the learning data and validation data again (2000 ~ 2008), applying the optimal parameters as in the previous validation. Finally, each corporate default prediction model is evaluated and compared using test data (2009) based on the trained models over nine years. Then, the usefulness of the corporate default prediction model based on the deep learning time series algorithm is proved. In addition, by adding the Lasso regression analysis to the existing methods (multiple discriminant analysis, logit model) which select the variables, it is proved that the deep learning time series algorithm model based on the three bundles of variables is useful for robust corporate default prediction. The definition of bankruptcy used is the same as that of Lee (2015). Independent variables include financial information such as financial ratios used in previous studies. Multivariate discriminant analysis, logit model, and Lasso regression model are used to select the optimal variable group. The influence of the Multivariate discriminant analysis model proposed by Altman (1968), the Logit model proposed by Ohlson (1980), the non-time series machine learning algorithms, and the deep learning time series algorithms are compared. In the case of corporate data, there are limitations of 'nonlinear variables', 'multi-collinearity' of variables, and 'lack of data'. While the logit model is nonlinear, the Lasso regression model solves the multi-collinearity problem, and the deep learning time series algorithm using the variable data generation method complements the lack of data. Big Data Technology, a leading technology in the future, is moving from simple human analysis, to automated AI analysis, and finally towards future intertwined AI applications. Although the study of the corporate default prediction model using the time series algorithm is still in its early stages, deep learning algorithm is much faster than regression analysis at corporate default prediction modeling. Also, it is more effective on prediction power. Through the Fourth Industrial Revolution, the current government and other overseas governments are working hard to integrate the system in everyday life of their nation and society. Yet the field of deep learning time series research for the financial industry is still insufficient. This is an initial study on deep learning time series algorithm analysis of corporate defaults. Therefore it is hoped that it will be used as a comparative analysis data for non-specialists who start a study combining financial data and deep learning time series algorithm.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.163-177
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• 2019

As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.